SlideShare ist ein Scribd-Unternehmen logo
1 von 23
Chapter 1: The Foundations:
Logic and Proofs
Discrete Mathematics and Its Applications
Lingma Acheson (linglu@iupui.edu)
Department of Computer and Information Science, IUPUI
1
1.1 Propositional Logic
A proposition is a declarative sentence (a
sentence that declares a fact) that is either
true or false, but not both.
Are the following sentences propositions?
Toronto is the capital of Canada.
Read this carefully.
1+2=3
x+1=2
What time is it?
(No)
(No)
(No)
(Yes)
(Yes)
Introduction
2
1.1 Propositional Logic
Propositional Logic – the area of logic that
deals with propositions
Propositional Variables – variables that
represent propositions: p, q, r, s
E.g. Proposition p – “Today is Friday.”
Truth values – T, F
3
1.1 Propositional Logic
 Examples
 Find the negation of the proposition “Today is Friday.” and
express this in simple English.
 Find the negation of the proposition “At least 10 inches of rain
fell today in Miami.” and express this in simple English.
DEFINITION 1
Let p be a proposition. The negation of p, denoted by ¬p, is the statement
“It is not the case that p.”
The proposition ¬p is read “not p.” The truth value of the negation of p, ¬p
is the opposite of the truth value of p.
Solution: The negation is “It is not the case that today is Friday.”
In simple English, “Today is not Friday.” or “It is not
Friday today.”
Solution: The negation is “It is not the case that at least 10 inches
of rain fell today in Miami.”
In simple English, “Less than 10 inches of rain fell today
in Miami.”
4
1.1 Propositional Logic
 Note: Always assume fixed times, fixed places, and particular people
unless otherwise noted.
 Truth table:
 Logical operators are used to form new propositions from two or more
existing propositions. The logical operators are also called
connectives.
The Truth Table for the
Negation of a Proposition.
p ¬p
T
F
F
T
5
1.1 Propositional Logic
 Examples
 Find the conjunction of the propositions p and q where p is the
proposition “Today is Friday.” and q is the proposition “It is
raining today.”, and the truth value of the conjunction.
DEFINITION 2
Let p and q be propositions. The conjunction of p and q, denoted by p
Λ q, is the proposition “p and q”. The conjunction p Λ q is true when
both p and q are true and is false otherwise.
Solution: The conjunction is the proposition “Today is Friday and it
is raining today.” The proposition is true on rainy Fridays.
6
1.1 Propositional Logic
 Note:
inclusive or : The disjunction is true when at least one of the two
propositions is true.
 E.g. “Students who have taken calculus or computer science can take
this class.” – those who take one or both classes.
exclusive or : The disjunction is true only when one of the
proposition is true.
 E.g. “Students who have taken calculus or computer science, but not
both, can take this class.” – only those who take one of them.
 Definition 3 uses inclusive or.
DEFINITION 3
Let p and q be propositions. The disjunction of p and q, denoted by p ν
q, is the proposition “p or q”. The conjunction p ν q is false when both
p and q are false and is true otherwise.
7
1.1 Propositional Logic

The Truth Table for
the Conjunction of
Two Propositions.
p q p Λ q
T T
T F
F T
F F
T
F
F
F
The Truth Table for
the Disjunction of
Two Propositions.
p q p ν q
T T
T F
F T
F F
T
T
T
F
DEFINITION 4
Let p and q be propositions. The exclusive or of p and q, denoted by p q,
is the proposition that is true when exactly one of p and q is true and is
false otherwise.
The Truth Table for the
Exclusive Or (XOR) of
Two Propositions.
p q p q
T T
T F
F T
F F
F
T
T
F


8
1.1 Propositional Logic

DEFINITION 5
Let p and q be propositions. The conditional statement p → q, is the
proposition “if p, then q.” The conditional statement is false when p is
true and q is false, and true otherwise. In the conditional statement p
→ q, p is called the hypothesis (or antecedent or premise) and q is
called the conclusion (or consequence).
Conditional Statements
 A conditional statement is also called an implication.
 Example: “If I am elected, then I will lower taxes.” p → q
implication:
elected, lower taxes. T T | T
not elected, lower taxes. F T | T
not elected, not lower taxes. F F | T
elected, not lower taxes. T F | F
9
1.1 Propositional Logic
 Example:
 Let p be the statement “Maria learns discrete mathematics.” and
q the statement “Maria will find a good job.” Express the
statement p → q as a statement in English.
Solution: Any of the following -
“If Maria learns discrete mathematics, then she will find a
good job.
“Maria will find a good job when she learns discrete
mathematics.”
“For Maria to get a good job, it is sufficient for her to
learn discrete mathematics.”
“Maria will find a good job unless she does not learn
discrete mathematics.”
10
1.1 Propositional Logic
 Other conditional statements:
 Converse of p → q : q → p
 Contrapositive of p → q : ¬ q → ¬ p
 Inverse of p → q : ¬ p → ¬ q
11
1.1 Propositional Logic
 p ↔ q has the same truth value as (p → q) Λ (q → p)
 “if and only if” can be expressed by “iff”
 Example:
 Let p be the statement “You can take the flight” and let q be the
statement “You buy a ticket.” Then p ↔ q is the statement
“You can take the flight if and only if you buy a ticket.”
Implication:
If you buy a ticket you can take the flight.
If you don’t buy a ticket you cannot take the flight.
DEFINITION 6
Let p and q be propositions. The biconditional statement p ↔ q is the
proposition “p if and only if q.” The biconditional statement p ↔ q is
true when p and q have the same truth values, and is false otherwise.
Biconditional statements are also called bi-implications.
12
1.1 Propositional Logic
The Truth Table for the
Biconditional p ↔ q.
p q p ↔ q
T T
T F
F T
F F
T
F
F
T
13
1.1 Propositional Logic
 We can use connectives to build up complicated compound
propositions involving any number of propositional variables, then
use truth tables to determine the truth value of these compound
propositions.
 Example: Construct the truth table of the compound proposition
(p ν ¬q) → (p Λ q).
Truth Tables of Compound Propositions
The Truth Table of (p ν ¬q) → (p Λ q).
p q ¬q p ν ¬q p Λ q (p ν ¬q) → (p Λ q)
T T
T F
F T
F F
F
T
F
T
T
T
F
T
T
F
F
F
T
F
T
F 14
1.1 Propositional Logic
 We can use parentheses to specify the order in which logical
operators in a compound proposition are to be applied.
 To reduce the number of parentheses, the precedence order is
defined for logical operators.
Precedence of Logical Operators
Precedence of Logical Operators.
Operator Precedence
¬ 1
Λ
ν
2
3
→
↔
4
5
E.g. ¬p Λ q = (¬p ) Λ q
p Λ q ν r = (p Λ q ) ν r
p ν q Λ r = p ν (q Λ r)
15
1.1 Propositional Logic
 English (and every other human language) is often ambiguous.
Translating sentences into compound statements removes the
ambiguity.
 Example: How can this English sentence be translated into a logical
expression?
“You cannot ride the roller coaster if you are under 4 feet
tall unless you are older than 16 years old.”
Translating English Sentences
Solution: Let q, r, and s represent “You can ride the roller coaster,”
“You are under 4 feet tall,” and “You are older than
16 years old.” The sentence can be translated into:
(r Λ ¬ s) → ¬q.
16
1.1 Propositional Logic
 Example: How can this English sentence be translated into a logical
expression?
“You can access the Internet from campus only if you are a
computer science major or you are not a freshman.”
Solution: Let a, c, and f represent “You can access the Internet from
campus,” “You are a computer science major,” and “You are
a freshman.” The sentence can be translated into:
a → (c ν ¬f).
17
1.1 Propositional Logic
 Computers represent information using bits.
 A bit is a symbol with two possible values, 0 and 1.
 By convention, 1 represents T (true) and 0 represents F (false).
 A variable is called a Boolean variable if its value is either true or
false.
 Bit operation – replace true by 1 and false by 0 in logical
operations.
Table for the Bit Operators OR, AND, and XOR.
x y x ν y x Λ y x y
0
0
1
1
0
1
0
1
0
1
1
1
0
0
0
1
0
1
1
0
Logic and Bit Operations

18
1.1 Propositional Logic
 Example: Find the bitwise OR, bitwise AND, and bitwise XOR of the
bit string 01 1011 0110 and 11 0001 1101.
DEFINITION 7
A bit string is a sequence of zero or more bits. The length of this string
is the number of bits in the string.
Solution:
01 1011 0110
11 0001 1101
-------------------
11 1011 1111 bitwise OR
01 0001 0100 bitwise AND
10 1010 1011 bitwise XOR
19
1.2 Propositional Equivalences
DEFINITION 1
A compound proposition that is always true, no matter what the truth
values of the propositions that occurs in it, is called a tautology. A
compound proposition that is always false is called a contradiction. A
compound proposition that is neither a tautology or a contradiction is
called a contingency.
Introduction
Examples of a Tautology and a Contradiction.
p ¬p p ν ¬p p Λ ¬p
T
F
F
T
T
T
F
F
20
1.2 Propositional Equivalences
DEFINITION 2
The compound propositions p and q are called logically equivalent if p ↔
q is a tautology. The notation p ≡ q denotes that p and q are logically
equivalent.
Logical Equivalences
Truth Tables for ¬p ν q and p → q .
p q ¬p ¬p ν q p → q
T
T
F
F
T
F
T
F
F
F
T
T
T
F
T
T
T
F
T
T
 Compound propositions that have the same truth values in all
possible cases are called logically equivalent.
 Example: Show that ¬p ν q and p → q are logically equivalent.
21
1.2 Propositional Equivalences
 In general, 2n rows are required if a compound proposition involves n
propositional variables in order to get the combination of all truth
values.
 See page 24, 25 for more logical equivalences.
22
1.2 Propositional Equivalences
Constructing New Logical Equivalences
 Example: Show that ¬(p → q ) and p Λ ¬q are logically equivalent.
Solution:
¬(p → q ) ≡ ¬(¬p ν q) by example on slide 21
≡ ¬(¬p) Λ ¬q by the second De Morgan law
≡ p Λ ¬q by the double negation law
 Example: Show that (p Λ q) → (p ν q) is a tautology.
Solution: To show that this statement is a tautology, we will use logical
equivalences to demonstrate that it is logically equivalent to T.
(p Λ q) → (p ν q) ≡ ¬(p Λ q) ν (p ν q) by example on slide 21
≡ (¬ p ν ¬q) ν (p ν q) by the first De Morgan law
≡ (¬ p ν p) ν (¬ q ν q) by the associative and
communicative law for disjunction
≡ T ν T
≡ T
 Note: The above examples can also be done using truth tables.
23

Weitere ähnliche Inhalte

Ähnlich wie lectures in prolog in order to advance in artificial intelligence

logicproof-141212042039-conversion-gate01.pdf
logicproof-141212042039-conversion-gate01.pdflogicproof-141212042039-conversion-gate01.pdf
logicproof-141212042039-conversion-gate01.pdf
PradeeshSAI
 
S2 1
S2 1S2 1
S2 1
IIUM
 
Disrete mathematics and_its application_by_rosen _7th edition_lecture_1
Disrete mathematics and_its application_by_rosen _7th edition_lecture_1Disrete mathematics and_its application_by_rosen _7th edition_lecture_1
Disrete mathematics and_its application_by_rosen _7th edition_lecture_1
taimoor iftikhar
 
20220818151924_PPT01 - The Logic of Compound and Quantitative Statement.pptx
20220818151924_PPT01 - The Logic of Compound and Quantitative Statement.pptx20220818151924_PPT01 - The Logic of Compound and Quantitative Statement.pptx
20220818151924_PPT01 - The Logic of Compound and Quantitative Statement.pptx
ssuser92109d
 
Discrete-Chapter 04 Logic Part I
Discrete-Chapter 04 Logic Part IDiscrete-Chapter 04 Logic Part I
Discrete-Chapter 04 Logic Part I
Wongyos Keardsri
 

Ähnlich wie lectures in prolog in order to advance in artificial intelligence (20)

UGC NET Computer Science & Application book.pdf [Sample]
UGC NET Computer Science & Application book.pdf  [Sample]UGC NET Computer Science & Application book.pdf  [Sample]
UGC NET Computer Science & Application book.pdf [Sample]
 
Per3 logika&pembuktian
Per3 logika&pembuktianPer3 logika&pembuktian
Per3 logika&pembuktian
 
Drinkfromme.pptx
Drinkfromme.pptxDrinkfromme.pptx
Drinkfromme.pptx
 
Logic&proof
Logic&proofLogic&proof
Logic&proof
 
logicproof-141212042039-conversion-gate01.pdf
logicproof-141212042039-conversion-gate01.pdflogicproof-141212042039-conversion-gate01.pdf
logicproof-141212042039-conversion-gate01.pdf
 
Chapter 1
Chapter 1Chapter 1
Chapter 1
 
Chapter 1
Chapter 1Chapter 1
Chapter 1
 
desmath(1).ppt
desmath(1).pptdesmath(1).ppt
desmath(1).ppt
 
Logic in Computer Science Unit 2 (1).pptx
Logic in Computer Science Unit 2 (1).pptxLogic in Computer Science Unit 2 (1).pptx
Logic in Computer Science Unit 2 (1).pptx
 
Slide subtopic 1
Slide subtopic 1Slide subtopic 1
Slide subtopic 1
 
Mathematical Logic - Part 1
Mathematical Logic - Part 1Mathematical Logic - Part 1
Mathematical Logic - Part 1
 
S2 1
S2 1S2 1
S2 1
 
DMS UNIT-1 ppt.pptx
DMS UNIT-1 ppt.pptxDMS UNIT-1 ppt.pptx
DMS UNIT-1 ppt.pptx
 
Chapter1p1 2.pptx
Chapter1p1 2.pptxChapter1p1 2.pptx
Chapter1p1 2.pptx
 
DS Lecture 2.ppt
DS Lecture 2.pptDS Lecture 2.ppt
DS Lecture 2.ppt
 
Disrete mathematics and_its application_by_rosen _7th edition_lecture_1
Disrete mathematics and_its application_by_rosen _7th edition_lecture_1Disrete mathematics and_its application_by_rosen _7th edition_lecture_1
Disrete mathematics and_its application_by_rosen _7th edition_lecture_1
 
20220818151924_PPT01 - The Logic of Compound and Quantitative Statement.pptx
20220818151924_PPT01 - The Logic of Compound and Quantitative Statement.pptx20220818151924_PPT01 - The Logic of Compound and Quantitative Statement.pptx
20220818151924_PPT01 - The Logic of Compound and Quantitative Statement.pptx
 
Discrete-Chapter 04 Logic Part I
Discrete-Chapter 04 Logic Part IDiscrete-Chapter 04 Logic Part I
Discrete-Chapter 04 Logic Part I
 
Unit I discrete mathematics lecture notes
Unit I  discrete mathematics lecture notesUnit I  discrete mathematics lecture notes
Unit I discrete mathematics lecture notes
 
Propositional logic
Propositional logicPropositional logic
Propositional logic
 

Kürzlich hochgeladen

一比一原版麦考瑞大学毕业证成绩单如何办理
一比一原版麦考瑞大学毕业证成绩单如何办理一比一原版麦考瑞大学毕业证成绩单如何办理
一比一原版麦考瑞大学毕业证成绩单如何办理
cyebo
 
NO1 Best Kala Jadu Expert Specialist In Germany Kala Jadu Expert Specialist I...
NO1 Best Kala Jadu Expert Specialist In Germany Kala Jadu Expert Specialist I...NO1 Best Kala Jadu Expert Specialist In Germany Kala Jadu Expert Specialist I...
NO1 Best Kala Jadu Expert Specialist In Germany Kala Jadu Expert Specialist I...
Amil baba
 
如何办理(UPenn毕业证书)宾夕法尼亚大学毕业证成绩单本科硕士学位证留信学历认证
如何办理(UPenn毕业证书)宾夕法尼亚大学毕业证成绩单本科硕士学位证留信学历认证如何办理(UPenn毕业证书)宾夕法尼亚大学毕业证成绩单本科硕士学位证留信学历认证
如何办理(UPenn毕业证书)宾夕法尼亚大学毕业证成绩单本科硕士学位证留信学历认证
acoha1
 
一比一原版(Monash毕业证书)莫纳什大学毕业证成绩单如何办理
一比一原版(Monash毕业证书)莫纳什大学毕业证成绩单如何办理一比一原版(Monash毕业证书)莫纳什大学毕业证成绩单如何办理
一比一原版(Monash毕业证书)莫纳什大学毕业证成绩单如何办理
pyhepag
 
Audience Researchndfhcvnfgvgbhujhgfv.pptx
Audience Researchndfhcvnfgvgbhujhgfv.pptxAudience Researchndfhcvnfgvgbhujhgfv.pptx
Audience Researchndfhcvnfgvgbhujhgfv.pptx
Stephen266013
 
1:1原版定制伦敦政治经济学院毕业证(LSE毕业证)成绩单学位证书留信学历认证
1:1原版定制伦敦政治经济学院毕业证(LSE毕业证)成绩单学位证书留信学历认证1:1原版定制伦敦政治经济学院毕业证(LSE毕业证)成绩单学位证书留信学历认证
1:1原版定制伦敦政治经济学院毕业证(LSE毕业证)成绩单学位证书留信学历认证
dq9vz1isj
 

Kürzlich hochgeladen (20)

2024 Q2 Orange County (CA) Tableau User Group Meeting
2024 Q2 Orange County (CA) Tableau User Group Meeting2024 Q2 Orange County (CA) Tableau User Group Meeting
2024 Q2 Orange County (CA) Tableau User Group Meeting
 
一比一原版麦考瑞大学毕业证成绩单如何办理
一比一原版麦考瑞大学毕业证成绩单如何办理一比一原版麦考瑞大学毕业证成绩单如何办理
一比一原版麦考瑞大学毕业证成绩单如何办理
 
NO1 Best Kala Jadu Expert Specialist In Germany Kala Jadu Expert Specialist I...
NO1 Best Kala Jadu Expert Specialist In Germany Kala Jadu Expert Specialist I...NO1 Best Kala Jadu Expert Specialist In Germany Kala Jadu Expert Specialist I...
NO1 Best Kala Jadu Expert Specialist In Germany Kala Jadu Expert Specialist I...
 
Jual Obat Aborsi Bandung (Asli No.1) Wa 082134680322 Klinik Obat Penggugur Ka...
Jual Obat Aborsi Bandung (Asli No.1) Wa 082134680322 Klinik Obat Penggugur Ka...Jual Obat Aborsi Bandung (Asli No.1) Wa 082134680322 Klinik Obat Penggugur Ka...
Jual Obat Aborsi Bandung (Asli No.1) Wa 082134680322 Klinik Obat Penggugur Ka...
 
Credit Card Fraud Detection: Safeguarding Transactions in the Digital Age
Credit Card Fraud Detection: Safeguarding Transactions in the Digital AgeCredit Card Fraud Detection: Safeguarding Transactions in the Digital Age
Credit Card Fraud Detection: Safeguarding Transactions in the Digital Age
 
Statistics Informed Decisions Using Data 5th edition by Michael Sullivan solu...
Statistics Informed Decisions Using Data 5th edition by Michael Sullivan solu...Statistics Informed Decisions Using Data 5th edition by Michael Sullivan solu...
Statistics Informed Decisions Using Data 5th edition by Michael Sullivan solu...
 
如何办理(UPenn毕业证书)宾夕法尼亚大学毕业证成绩单本科硕士学位证留信学历认证
如何办理(UPenn毕业证书)宾夕法尼亚大学毕业证成绩单本科硕士学位证留信学历认证如何办理(UPenn毕业证书)宾夕法尼亚大学毕业证成绩单本科硕士学位证留信学历认证
如何办理(UPenn毕业证书)宾夕法尼亚大学毕业证成绩单本科硕士学位证留信学历认证
 
一比一原版(Monash毕业证书)莫纳什大学毕业证成绩单如何办理
一比一原版(Monash毕业证书)莫纳什大学毕业证成绩单如何办理一比一原版(Monash毕业证书)莫纳什大学毕业证成绩单如何办理
一比一原版(Monash毕业证书)莫纳什大学毕业证成绩单如何办理
 
Bios of leading Astrologers & Researchers
Bios of leading Astrologers & ResearchersBios of leading Astrologers & Researchers
Bios of leading Astrologers & Researchers
 
Audience Researchndfhcvnfgvgbhujhgfv.pptx
Audience Researchndfhcvnfgvgbhujhgfv.pptxAudience Researchndfhcvnfgvgbhujhgfv.pptx
Audience Researchndfhcvnfgvgbhujhgfv.pptx
 
Digital Marketing Demystified: Expert Tips from Samantha Rae Coolbeth
Digital Marketing Demystified: Expert Tips from Samantha Rae CoolbethDigital Marketing Demystified: Expert Tips from Samantha Rae Coolbeth
Digital Marketing Demystified: Expert Tips from Samantha Rae Coolbeth
 
Data Visualization Exploring and Explaining with Data 1st Edition by Camm sol...
Data Visualization Exploring and Explaining with Data 1st Edition by Camm sol...Data Visualization Exploring and Explaining with Data 1st Edition by Camm sol...
Data Visualization Exploring and Explaining with Data 1st Edition by Camm sol...
 
What is Insertion Sort. Its basic information
What is Insertion Sort. Its basic informationWhat is Insertion Sort. Its basic information
What is Insertion Sort. Its basic information
 
Identify Rules that Predict Patient’s Heart Disease - An Application of Decis...
Identify Rules that Predict Patient’s Heart Disease - An Application of Decis...Identify Rules that Predict Patient’s Heart Disease - An Application of Decis...
Identify Rules that Predict Patient’s Heart Disease - An Application of Decis...
 
NOAM AAUG Adobe Summit 2024: Summit Slam Dunks
NOAM AAUG Adobe Summit 2024: Summit Slam DunksNOAM AAUG Adobe Summit 2024: Summit Slam Dunks
NOAM AAUG Adobe Summit 2024: Summit Slam Dunks
 
MATERI MANAJEMEN OF PENYAKIT TETANUS.ppt
MATERI  MANAJEMEN OF PENYAKIT TETANUS.pptMATERI  MANAJEMEN OF PENYAKIT TETANUS.ppt
MATERI MANAJEMEN OF PENYAKIT TETANUS.ppt
 
1:1原版定制伦敦政治经济学院毕业证(LSE毕业证)成绩单学位证书留信学历认证
1:1原版定制伦敦政治经济学院毕业证(LSE毕业证)成绩单学位证书留信学历认证1:1原版定制伦敦政治经济学院毕业证(LSE毕业证)成绩单学位证书留信学历认证
1:1原版定制伦敦政治经济学院毕业证(LSE毕业证)成绩单学位证书留信学历认证
 
Seven tools of quality control.slideshare
Seven tools of quality control.slideshareSeven tools of quality control.slideshare
Seven tools of quality control.slideshare
 
Atlantic Grupa Case Study (Mintec Data AI)
Atlantic Grupa Case Study (Mintec Data AI)Atlantic Grupa Case Study (Mintec Data AI)
Atlantic Grupa Case Study (Mintec Data AI)
 
The Significance of Transliteration Enhancing
The Significance of Transliteration EnhancingThe Significance of Transliteration Enhancing
The Significance of Transliteration Enhancing
 

lectures in prolog in order to advance in artificial intelligence

  • 1. Chapter 1: The Foundations: Logic and Proofs Discrete Mathematics and Its Applications Lingma Acheson (linglu@iupui.edu) Department of Computer and Information Science, IUPUI 1
  • 2. 1.1 Propositional Logic A proposition is a declarative sentence (a sentence that declares a fact) that is either true or false, but not both. Are the following sentences propositions? Toronto is the capital of Canada. Read this carefully. 1+2=3 x+1=2 What time is it? (No) (No) (No) (Yes) (Yes) Introduction 2
  • 3. 1.1 Propositional Logic Propositional Logic – the area of logic that deals with propositions Propositional Variables – variables that represent propositions: p, q, r, s E.g. Proposition p – “Today is Friday.” Truth values – T, F 3
  • 4. 1.1 Propositional Logic  Examples  Find the negation of the proposition “Today is Friday.” and express this in simple English.  Find the negation of the proposition “At least 10 inches of rain fell today in Miami.” and express this in simple English. DEFINITION 1 Let p be a proposition. The negation of p, denoted by ¬p, is the statement “It is not the case that p.” The proposition ¬p is read “not p.” The truth value of the negation of p, ¬p is the opposite of the truth value of p. Solution: The negation is “It is not the case that today is Friday.” In simple English, “Today is not Friday.” or “It is not Friday today.” Solution: The negation is “It is not the case that at least 10 inches of rain fell today in Miami.” In simple English, “Less than 10 inches of rain fell today in Miami.” 4
  • 5. 1.1 Propositional Logic  Note: Always assume fixed times, fixed places, and particular people unless otherwise noted.  Truth table:  Logical operators are used to form new propositions from two or more existing propositions. The logical operators are also called connectives. The Truth Table for the Negation of a Proposition. p ¬p T F F T 5
  • 6. 1.1 Propositional Logic  Examples  Find the conjunction of the propositions p and q where p is the proposition “Today is Friday.” and q is the proposition “It is raining today.”, and the truth value of the conjunction. DEFINITION 2 Let p and q be propositions. The conjunction of p and q, denoted by p Λ q, is the proposition “p and q”. The conjunction p Λ q is true when both p and q are true and is false otherwise. Solution: The conjunction is the proposition “Today is Friday and it is raining today.” The proposition is true on rainy Fridays. 6
  • 7. 1.1 Propositional Logic  Note: inclusive or : The disjunction is true when at least one of the two propositions is true.  E.g. “Students who have taken calculus or computer science can take this class.” – those who take one or both classes. exclusive or : The disjunction is true only when one of the proposition is true.  E.g. “Students who have taken calculus or computer science, but not both, can take this class.” – only those who take one of them.  Definition 3 uses inclusive or. DEFINITION 3 Let p and q be propositions. The disjunction of p and q, denoted by p ν q, is the proposition “p or q”. The conjunction p ν q is false when both p and q are false and is true otherwise. 7
  • 8. 1.1 Propositional Logic  The Truth Table for the Conjunction of Two Propositions. p q p Λ q T T T F F T F F T F F F The Truth Table for the Disjunction of Two Propositions. p q p ν q T T T F F T F F T T T F DEFINITION 4 Let p and q be propositions. The exclusive or of p and q, denoted by p q, is the proposition that is true when exactly one of p and q is true and is false otherwise. The Truth Table for the Exclusive Or (XOR) of Two Propositions. p q p q T T T F F T F F F T T F   8
  • 9. 1.1 Propositional Logic  DEFINITION 5 Let p and q be propositions. The conditional statement p → q, is the proposition “if p, then q.” The conditional statement is false when p is true and q is false, and true otherwise. In the conditional statement p → q, p is called the hypothesis (or antecedent or premise) and q is called the conclusion (or consequence). Conditional Statements  A conditional statement is also called an implication.  Example: “If I am elected, then I will lower taxes.” p → q implication: elected, lower taxes. T T | T not elected, lower taxes. F T | T not elected, not lower taxes. F F | T elected, not lower taxes. T F | F 9
  • 10. 1.1 Propositional Logic  Example:  Let p be the statement “Maria learns discrete mathematics.” and q the statement “Maria will find a good job.” Express the statement p → q as a statement in English. Solution: Any of the following - “If Maria learns discrete mathematics, then she will find a good job. “Maria will find a good job when she learns discrete mathematics.” “For Maria to get a good job, it is sufficient for her to learn discrete mathematics.” “Maria will find a good job unless she does not learn discrete mathematics.” 10
  • 11. 1.1 Propositional Logic  Other conditional statements:  Converse of p → q : q → p  Contrapositive of p → q : ¬ q → ¬ p  Inverse of p → q : ¬ p → ¬ q 11
  • 12. 1.1 Propositional Logic  p ↔ q has the same truth value as (p → q) Λ (q → p)  “if and only if” can be expressed by “iff”  Example:  Let p be the statement “You can take the flight” and let q be the statement “You buy a ticket.” Then p ↔ q is the statement “You can take the flight if and only if you buy a ticket.” Implication: If you buy a ticket you can take the flight. If you don’t buy a ticket you cannot take the flight. DEFINITION 6 Let p and q be propositions. The biconditional statement p ↔ q is the proposition “p if and only if q.” The biconditional statement p ↔ q is true when p and q have the same truth values, and is false otherwise. Biconditional statements are also called bi-implications. 12
  • 13. 1.1 Propositional Logic The Truth Table for the Biconditional p ↔ q. p q p ↔ q T T T F F T F F T F F T 13
  • 14. 1.1 Propositional Logic  We can use connectives to build up complicated compound propositions involving any number of propositional variables, then use truth tables to determine the truth value of these compound propositions.  Example: Construct the truth table of the compound proposition (p ν ¬q) → (p Λ q). Truth Tables of Compound Propositions The Truth Table of (p ν ¬q) → (p Λ q). p q ¬q p ν ¬q p Λ q (p ν ¬q) → (p Λ q) T T T F F T F F F T F T T T F T T F F F T F T F 14
  • 15. 1.1 Propositional Logic  We can use parentheses to specify the order in which logical operators in a compound proposition are to be applied.  To reduce the number of parentheses, the precedence order is defined for logical operators. Precedence of Logical Operators Precedence of Logical Operators. Operator Precedence ¬ 1 Λ ν 2 3 → ↔ 4 5 E.g. ¬p Λ q = (¬p ) Λ q p Λ q ν r = (p Λ q ) ν r p ν q Λ r = p ν (q Λ r) 15
  • 16. 1.1 Propositional Logic  English (and every other human language) is often ambiguous. Translating sentences into compound statements removes the ambiguity.  Example: How can this English sentence be translated into a logical expression? “You cannot ride the roller coaster if you are under 4 feet tall unless you are older than 16 years old.” Translating English Sentences Solution: Let q, r, and s represent “You can ride the roller coaster,” “You are under 4 feet tall,” and “You are older than 16 years old.” The sentence can be translated into: (r Λ ¬ s) → ¬q. 16
  • 17. 1.1 Propositional Logic  Example: How can this English sentence be translated into a logical expression? “You can access the Internet from campus only if you are a computer science major or you are not a freshman.” Solution: Let a, c, and f represent “You can access the Internet from campus,” “You are a computer science major,” and “You are a freshman.” The sentence can be translated into: a → (c ν ¬f). 17
  • 18. 1.1 Propositional Logic  Computers represent information using bits.  A bit is a symbol with two possible values, 0 and 1.  By convention, 1 represents T (true) and 0 represents F (false).  A variable is called a Boolean variable if its value is either true or false.  Bit operation – replace true by 1 and false by 0 in logical operations. Table for the Bit Operators OR, AND, and XOR. x y x ν y x Λ y x y 0 0 1 1 0 1 0 1 0 1 1 1 0 0 0 1 0 1 1 0 Logic and Bit Operations  18
  • 19. 1.1 Propositional Logic  Example: Find the bitwise OR, bitwise AND, and bitwise XOR of the bit string 01 1011 0110 and 11 0001 1101. DEFINITION 7 A bit string is a sequence of zero or more bits. The length of this string is the number of bits in the string. Solution: 01 1011 0110 11 0001 1101 ------------------- 11 1011 1111 bitwise OR 01 0001 0100 bitwise AND 10 1010 1011 bitwise XOR 19
  • 20. 1.2 Propositional Equivalences DEFINITION 1 A compound proposition that is always true, no matter what the truth values of the propositions that occurs in it, is called a tautology. A compound proposition that is always false is called a contradiction. A compound proposition that is neither a tautology or a contradiction is called a contingency. Introduction Examples of a Tautology and a Contradiction. p ¬p p ν ¬p p Λ ¬p T F F T T T F F 20
  • 21. 1.2 Propositional Equivalences DEFINITION 2 The compound propositions p and q are called logically equivalent if p ↔ q is a tautology. The notation p ≡ q denotes that p and q are logically equivalent. Logical Equivalences Truth Tables for ¬p ν q and p → q . p q ¬p ¬p ν q p → q T T F F T F T F F F T T T F T T T F T T  Compound propositions that have the same truth values in all possible cases are called logically equivalent.  Example: Show that ¬p ν q and p → q are logically equivalent. 21
  • 22. 1.2 Propositional Equivalences  In general, 2n rows are required if a compound proposition involves n propositional variables in order to get the combination of all truth values.  See page 24, 25 for more logical equivalences. 22
  • 23. 1.2 Propositional Equivalences Constructing New Logical Equivalences  Example: Show that ¬(p → q ) and p Λ ¬q are logically equivalent. Solution: ¬(p → q ) ≡ ¬(¬p ν q) by example on slide 21 ≡ ¬(¬p) Λ ¬q by the second De Morgan law ≡ p Λ ¬q by the double negation law  Example: Show that (p Λ q) → (p ν q) is a tautology. Solution: To show that this statement is a tautology, we will use logical equivalences to demonstrate that it is logically equivalent to T. (p Λ q) → (p ν q) ≡ ¬(p Λ q) ν (p ν q) by example on slide 21 ≡ (¬ p ν ¬q) ν (p ν q) by the first De Morgan law ≡ (¬ p ν p) ν (¬ q ν q) by the associative and communicative law for disjunction ≡ T ν T ≡ T  Note: The above examples can also be done using truth tables. 23